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1 to 10 of 98 Results

Replication Data for: Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals Sep 6, 2024 - Institute of Applied Analysis and Numerical Simulation Bordignon, Andrea; Cances, Eric; Dusson, Geneviève; Kemlin, Gaspard; Lainez Reyes, Rafael; Stamm, Benjamin, 2024, "Replication Data for: Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals", https://doi.org/10.18419/darus-4469, DaRUS, V1 Data for reproducibility of the numerical simulations of the research paper "Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals". The .zip file contains everything needed to generate the plots shown in the p...
Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Sep 2, 2024 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing" Reichmann, Luca; Hägele, David; Weiskopf, Daniel, 2024, "Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions", https://doi.org/10.18419/darus-4441, DaRUS, V1, UNF:6:WoQ4MNffz92VcvZ/qCGL5w== [fileUNF] This dataset contains the supplemental material for "Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions". The contents and usage of this dataset are described in the README.md files.
Replication Data for: Partitioned Multiphysics Simulation of an Electrophysiological Three-Tendon-Biceps Model Aug 23, 2024 - Usability and Sustainability of Simulation Software Homs-Pons, Carme; Schneider, David; Simonis, Frédéric; Schulte, Miriam; Uekermann, Benjamin, 2024, "Replication Data for: Partitioned Multiphysics Simulation of an Electrophysiological Three-Tendon-Biceps Model", https://doi.org/10.18419/darus-4228, DaRUS, V1 This dataset contains software (preCICE v3.1.2, OpenDiHu, deal.II-based solver and ASTE) as well as setup files and instructions to reproduce the experiments "Partitioned Multiphysics Simulation of an Electrophysiological Three-Tendon-Biceps Model". The actual results of the expe...
Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data Aug 8, 2024 - PN 6-3 Holzmüller, David; Grinsztajn, Léo; Steinwart, Ingo, 2024, "Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data", https://doi.org/10.18419/darus-4255, DaRUS, V1 This dataset contains code and data for our paper "Better by default: Strong pre-tuned MLPs and boosted trees on tabular data". The main code is provided in pytabkit_code.zip and contains further documentation in README.md and the docs folder. The main code is also provided on Gi...
Coupled thermo-mechanical simulation results of a finite element discbrake Jul 29, 2024 - PN 7-6 Kneifl, Jonas; Rettberg, Johannes; Fehr, Jörg, 2024, "Coupled thermo-mechanical simulation results of a finite element discbrake", https://doi.org/10.18419/darus-4418, DaRUS, V1 Simulation Results of a Finite Element Discbrake The finite element model describes an academic representation of a heated discbrake. It is implemented in the commercial simulation software Abaqus. It is composed out of one layer of 60 elements resulting in a total of 146 nodes w...
Processes data and code for Dynamics of Lagrangian Sensor Particles Jul 29, 2024 - CHOLife_TUHH_LSP_tracking Rautenbach, Ryan; Buntkiel, Lukas; Schäfer, Jan; Hofmann, Sebastian, 2024, "Processes data and code for Dynamics of Lagrangian Sensor Particles", https://doi.org/10.18419/darus-4238, DaRUS, V1 This repository entails the data and Pythoncode for the publication "Dynamics of Lagrangian Sensor Particles: The Effect of Non-Homogeneous Mass Distribution" in the journal "Processes". In the following a brief introduction and guide based on the folders in the repository is lai...
Code for Faithful Embeddings for EL++ Knowledge Bases Jul 5, 2024 - KnowGraphs (EU) Xiong, Bo; Potyka, Nico; Tran, Trung-Kien; Nayyeri, Mojtaba; Staab, Steffen, 2024, "Code for Faithful Embeddings for EL++ Knowledge Bases", https://doi.org/10.18419/darus-3989, DaRUS, V1 This is the official pytorch implementation of the paper "Faithful embeddings for EL++ Knowledge Bases" published in ISWC 2022. The code was implemented based on el-embeddings. The code can be used to reproduce the experiments on subsumption reasoning. To execute the code, follow...
Code for Hyperbolic Embedding Inference for Structured Multi-Label Prediction Jul 5, 2024 - KnowGraphs (EU) Xiong, Bo; Nayyeri, Mojtaba; Cochez, Michael; Staab, Steffen, 2024, "Code for Hyperbolic Embedding Inference for Structured Multi-Label Prediction", https://doi.org/10.18419/darus-3988, DaRUS, V1 This is a PyTorch implementation of the paper Hyperbolic Embedding Inference for Structured Multi-Label Prediction published in NeurIPS 2022. The code provides the Python scripts to reproduce the experiments in the paper, as well as a proof-of-concept example of the method. To ex...
Replication Data for NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24) Jul 5, 2024 - KnowGraphs (EU) Xiong, Bo; Nayyeri, Mojtaba; Luo, Linhao; Wang, Zihao; Pan, Shirui; Staab, Steffen, 2024, "Replication Data for NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24)", https://doi.org/10.18419/darus-3978, DaRUS, V1 This code is a PyTorch implementation of the paper "NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24)". NestE is a knowledge graph embedding method that can encode nested facts represented by quoted triples (h,r,t) in which the subject and objec...
Code for Ultrahyperbolic Knowledge Graph Embeddings Jul 5, 2024 - KnowGraphs (EU) Xiong, Bo; Zhu, Shichao; Nayyeri, Mojtaba; Xu, Chengjin; Pan, Shirui; Staab, Steffen, 2024, "Code for Ultrahyperbolic Knowledge Graph Embeddings", https://doi.org/10.18419/darus-4342, DaRUS, V1 This is a Pytorch implementation of the paper Ultrahyperbolic Knowledge Graph Embeddings published in KDD 2022. This code is used to reproduce the experiments of the method UltraE, a geometric embedding approach for knowledge graph embeddings. The code is tested on public dataset...

Replication Data for: Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals

Sep 6, 2024 - Institute of Applied Analysis and Numerical Simulation

Bordignon, Andrea; Cances, Eric; Dusson, Geneviève; Kemlin, Gaspard; Lainez Reyes, Rafael; Stamm, Benjamin, 2024, "Replication Data for: Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals", https://doi.org/10.18419/darus-4469, DaRUS, V1

Data for reproducibility of the numerical simulations of the research paper "Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals". The .zip file contains everything needed to generate the plots shown in the p...

Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions

Sep 2, 2024 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"

Reichmann, Luca; Hägele, David; Weiskopf, Daniel, 2024, "Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions", https://doi.org/10.18419/darus-4441, DaRUS, V1, UNF:6:WoQ4MNffz92VcvZ/qCGL5w== [fileUNF]

This dataset contains the supplemental material for "Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions". The contents and usage of this dataset are described in the README.md files.

Replication Data for: Partitioned Multiphysics Simulation of an Electrophysiological Three-Tendon-Biceps Model

Aug 23, 2024 - Usability and Sustainability of Simulation Software

Homs-Pons, Carme; Schneider, David; Simonis, Frédéric; Schulte, Miriam; Uekermann, Benjamin, 2024, "Replication Data for: Partitioned Multiphysics Simulation of an Electrophysiological Three-Tendon-Biceps Model", https://doi.org/10.18419/darus-4228, DaRUS, V1

This dataset contains software (preCICE v3.1.2, OpenDiHu, deal.II-based solver and ASTE) as well as setup files and instructions to reproduce the experiments "Partitioned Multiphysics Simulation of an Electrophysiological Three-Tendon-Biceps Model". The actual results of the expe...

Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

Aug 8, 2024 - PN 6-3

Holzmüller, David; Grinsztajn, Léo; Steinwart, Ingo, 2024, "Code and Data for: Better by default: Strong pre-tuned MLPs and boosted trees on tabular data", https://doi.org/10.18419/darus-4255, DaRUS, V1

This dataset contains code and data for our paper "Better by default: Strong pre-tuned MLPs and boosted trees on tabular data". The main code is provided in pytabkit_code.zip and contains further documentation in README.md and the docs folder. The main code is also provided on Gi...

Coupled thermo-mechanical simulation results of a finite element discbrake

Jul 29, 2024 - PN 7-6

Kneifl, Jonas; Rettberg, Johannes; Fehr, Jörg, 2024, "Coupled thermo-mechanical simulation results of a finite element discbrake", https://doi.org/10.18419/darus-4418, DaRUS, V1

Simulation Results of a Finite Element Discbrake The finite element model describes an academic representation of a heated discbrake. It is implemented in the commercial simulation software Abaqus. It is composed out of one layer of 60 elements resulting in a total of 146 nodes w...

Processes data and code for Dynamics of Lagrangian Sensor Particles

Jul 29, 2024 - CHOLife_TUHH_LSP_tracking

Rautenbach, Ryan; Buntkiel, Lukas; Schäfer, Jan; Hofmann, Sebastian, 2024, "Processes data and code for Dynamics of Lagrangian Sensor Particles", https://doi.org/10.18419/darus-4238, DaRUS, V1

This repository entails the data and Pythoncode for the publication "Dynamics of Lagrangian Sensor Particles: The Effect of Non-Homogeneous Mass Distribution" in the journal "Processes". In the following a brief introduction and guide based on the folders in the repository is lai...

Code for Faithful Embeddings for EL++ Knowledge Bases

Jul 5, 2024 - KnowGraphs (EU)

Xiong, Bo; Potyka, Nico; Tran, Trung-Kien; Nayyeri, Mojtaba; Staab, Steffen, 2024, "Code for Faithful Embeddings for EL++ Knowledge Bases", https://doi.org/10.18419/darus-3989, DaRUS, V1

This is the official pytorch implementation of the paper "Faithful embeddings for EL++ Knowledge Bases" published in ISWC 2022. The code was implemented based on el-embeddings. The code can be used to reproduce the experiments on subsumption reasoning. To execute the code, follow...

Code for Hyperbolic Embedding Inference for Structured Multi-Label Prediction

Jul 5, 2024 - KnowGraphs (EU)

Xiong, Bo; Nayyeri, Mojtaba; Cochez, Michael; Staab, Steffen, 2024, "Code for Hyperbolic Embedding Inference for Structured Multi-Label Prediction", https://doi.org/10.18419/darus-3988, DaRUS, V1

This is a PyTorch implementation of the paper Hyperbolic Embedding Inference for Structured Multi-Label Prediction published in NeurIPS 2022. The code provides the Python scripts to reproduce the experiments in the paper, as well as a proof-of-concept example of the method. To ex...

Replication Data for NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24)

Jul 5, 2024 - KnowGraphs (EU)

Xiong, Bo; Nayyeri, Mojtaba; Luo, Linhao; Wang, Zihao; Pan, Shirui; Staab, Steffen, 2024, "Replication Data for NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24)", https://doi.org/10.18419/darus-3978, DaRUS, V1

This code is a PyTorch implementation of the paper "NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24)". NestE is a knowledge graph embedding method that can encode nested facts represented by quoted triples (h,r,t) in which the subject and objec...

Code for Ultrahyperbolic Knowledge Graph Embeddings

Jul 5, 2024 - KnowGraphs (EU)

Xiong, Bo; Zhu, Shichao; Nayyeri, Mojtaba; Xu, Chengjin; Pan, Shirui; Staab, Steffen, 2024, "Code for Ultrahyperbolic Knowledge Graph Embeddings", https://doi.org/10.18419/darus-4342, DaRUS, V1

This is a Pytorch implementation of the paper Ultrahyperbolic Knowledge Graph Embeddings published in KDD 2022. This code is used to reproduce the experiments of the method UltraE, a geometric embedding approach for knowledge graph embeddings. The code is tested on public dataset...

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